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\section{Introduction}
The Web provides a wealth of information to the world through multiple forms of media and has been expanding rapidly ever since its inception. To help navigate through the ever growing amount of semi-structured data available on the Web, search engines have been constructed to answer user queries of any kind. The page results returned to the user are ranked according to relevance, freshness, and popularity with respect to the provided information. While this form of search can quickly lead users to relevant information, the user is still faced with numerous pages to assimilate on their own. To further facilitate the exploration of information provided on the Web, we present ChronoSearch: A System for Extracting a Chronological Timeline for a Provided Entity.

While manually generated timelines are available on the Web, our evaluation shows that the quality of these timelines can be improved upon. Manually generated timelines suffer from authors with subjective input, they pertain only to a specific series of events, and are often not updated with the latest events. ChronoSearch aims to remove the weaknesses that are present in manually generated timelines by providing the user a dynamically generated objective timeline that relates to the input person entity provided.

Temporal information is both useful and important due to the fact that every event can theoretically be associated with a time. Time is an absolutely crucial attribute that can be associated with all things in life, and therefore our system plays a critical role in the field of data extraction and information gathering. Time is continually changing, and even in today's world, events can be tied to a specific time of interest no matter what geographical associations can be made with that event. Time provides a necessary boundary and unique identifier for any event that can currently be described in the natural world. As we continue to forever make history, the importance of temporal information will be undoubtedly useful to describe any piece of data associated with an entity.

For example, suppose a user is interested in learning about Steve Jobs. Given the recent events, the majority of the top ranked pages returned from a search engine would contain information about Jobs’ death. With the large number of top ranked pages being dedicated to the popularity of the recent events, users would be forced to browse through hundreds of pages before finding information about Jobs outside of Apple. Using ChronoSearch, users would be presented with a timeline of information pertaining to Jobs. Jobs’ resignation from Apple, his death, and other recent events would still appear on the timeline created by ChronoSearch. However, links to other events in his career would also be displayed along the timeline allowing users to quickly skim over events and build a thorough profile of Jobs’ life. 

Social networking provider, Facebook, has also realized the value of displaying information along a timeline. During the research period of this work, Facebook launched their own timeline application that enables users to build timelines from the data they already have in their profile. In \cite{Lessin:2011:Online}, Facebook describes the importance of this application as, \begin{quote}\textit{A home for all the great stories you’ve already shared. They don’t just vanish as you add new stuff. The way your profile works today, 99\% of the stories you share vanish. The only way to find the posts that matter is to click ‘Older Posts’ at the bottom of the page. Again. And again.}\end{quote}
Instead of gathering data from user profiles, the system we are proposing gathers data pertaining to a specific person entity from the Web and extracts, organizes, and displays relevant temporal information. 

More specifically, we define our problem in terms of input and output as:

\begin{description}
\item[input] an entity, \textit{E}, and a set of web pages, \textit{W}, related to \textit{E}. It should be emphasized that \textit{W} only contains pages related to \textit{E}; entity disambiguation is not a focus of this research. 
\item[output] A sorted list of event descriptions related to \textit{E}, \textit{L}. \textit{L} = \{ $l_{i} | l_{i}$ occurred before $l_{i+1}$\}.
\end{description}
Where each $ l_{i}$
\begin{enumerate}
\item Is a sentence describing an event.
\item Describes a unique event.
\item Contains a link to the source web page belonging to \textit{W}.
\end{enumerate}
Further, the set of events, \textit{L}, should be:
\begin{description}
\item[Precise] Each $ l_{i}$ describes an event the user is interested in.
\item[Comprehensive] \textit{L} contains a description of all the events pertaining to \textit{E}.
\end{description}

The main contribution of this work for the research community is a unique event and temporal information extraction approach applied to the Web. The approach demonstrates that the redundancy present on the Web can be utilized to focus on only the strongest extraction signals that provide the highest level of precision. This paper also provides implementation difficulties, a working prototype, and an evaluation methodology for automatically generated timelines.

The rest of the paper is structured as follows. Section \ref{sec:Design} presents the design of our system followed by section \ref{sec:Implementation}, which describes the implementation of the design. The implementation section also includes difficulties and accomplishments. The implemented prototype is then evaluated using our evaluation method described in Section \ref{sec:Evaluation}. Section \ref{sec:LessonsLearned} follows with lessons learned which includes a failure analysis of a preliminary design decision. Finally, the paper lays out a future research path aimed at improving ChronoSearch in Section \ref{sec:FutureResearch}. 

